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The Journal of Neuroscience, February 19, 2014 • 34(8):3101–3117 • 3101
Systems/Circuits
Cortical and Thalamic Excitation Mediate the Multiphasic
Responses of Striatal Cholinergic Interneurons to
Motivationally Salient Stimuli
Natalie M. Doig,1 Peter J. Magill,1 Paul Apicella,2 J. Paul Bolam,1 and Andrew Sharott1
1
Medical Research Council Anatomical Neuropharmacology Unit, Department of Pharmacology, University of Oxford, Oxford OX1 3TH, United Kingdom;
and 2Institut de Neurosciences de la Timone, Centre National de la Recherche Scientifique-Aix-Marseille Université, 13005 Marseille, France
Cholinergic interneurons are key components of striatal microcircuits. In primates, tonically active neurons (putative cholinergic interneurons) exhibit multiphasic responses to motivationally salient stimuli that mirror those of midbrain dopamine neurons and
together these two systems mediate reward-related learning in basal ganglia circuits. Here, we addressed the potential contribution of
cortical and thalamic excitatory inputs to the characteristic multiphasic responses of cholinergic interneurons in vivo. We first recorded
and labeled individual cholinergic interneurons in anesthetized rats. Electron microscopic analyses of these labeled neurons demonstrated that an individual interneuron could form synapses with cortical and, more commonly, thalamic afferents. Single-pulse electrical
stimulation of ipsilateral frontal cortex led to robust short-latency (⬍20 ms) interneuron spiking, indicating monosynaptic connectivity,
but firing probability progressively decreased during high-frequency pulse trains. In contrast, single-pulse thalamic stimulation led to
weak short-latency spiking, but firing probability increased during pulse trains. After initial excitation from cortex or thalamus, interneurons displayed a “pause” in firing, followed by a “rebound” increase in firing rate. Across all stimulation protocols, the number of spikes
in the initial excitation correlated positively with pause duration and negatively with rebound magnitude. The magnitude of the initial
excitation, therefore, partly determined the profile of later components of multiphasic responses. Upon examining the responses of
tonically active neurons in behaving primates, we found that these correlations held true for unit responses to a reward-predicting
stimulus, but not to the reward alone, delivered outside of any task. We conclude that excitatory inputs determine, at least in part, the
multiphasic responses of cholinergic interneurons under specific behavioral conditions.
Key words: basal ganglia; corticostriatal; parafascicular nucleus; thalamostriatal; tonically active neuron
Introduction
The striatum is the principal site of integration of cortical and
thalamic information in the basal ganglia. Although mediumsized spiny projection neurons (MSNs) are the main target of
both cortical and thalamic projections (Somogyi et al., 1981;
Dubé et al., 1988; Doig et al., 2010), certain types of interneurons
are selectively targeted by cortical and/or thalamic afferents, so
these glutamatergic inputs can powerfully influence the output of
the striatum (Mallet et al., 2005; Ding et al., 2010). Cholinergic
Received Oct. 28, 2013; revised Jan. 17, 2014; accepted Jan. 23, 2014.
Author contributions: N.M.D., P.J.M., J.P.B., and A.S. designed research; N.M.D., P.A., and A.S. performed research; A.S. analyzed data; N.M.D. and A.S. wrote the paper.
This work was supported by the Medical Research Council UK (Grants U138197109 and U138164490), Parkinson’s
UK (Grant G-0806), a Marie Curie European Re-integration Grant (SNAP-PD) awarded by the European Union, and an
International Joint Project Grant (Grant JP090457) awarded by The Royal Society. N.M.D. was in receipt of a Medical
Research Council studentship. We thank J. Morgan for the generous gift of antibodies against Cerebellin-1; G. Hazell,
B. Micklem, L. Norman, K. Whitworth, and C. Johnson for technical support; I. Huerta-Ocampo and K. Nakamura for
advice and assistance with immunohistochemistry; F. Vinciati for contributing to electrophysiological recordings;
members of the Apicella laboratory for help with TAN data collection; and P. Henny for assistance with EM analysis
and helpful comments on the manuscript.
Correspondence should be addressed to Andrew Sharott, MRC Anatomical Neuropharmacology Unit, Department
of Pharmacology, Mansfield Road, Oxford OX1 3TH, United Kingdom. E-mail: [email protected].
DOI:10.1523/JNEUROSCI.4627-13.2014
Copyright © 2014 the authors 0270-6474/14/343101-17$15.00/0
interneurons are prime candidates for mediating the effects of
excitatory inputs to striatum and have been studied extensively in
relation to reinforcement learning through their putative identification as “tonically active neurons” (TANs) in behaving animals.
TANs are particularly sensitive to motivationally salient stimuli, usually responding with a pause in their tonic firing that can be preceded
by short-latency firing and/or followed by a “rebound” increase in
spiking (Morris et al., 2004; Joshua et al., 2008). The timing of these
responses is entwined with those of midbrain dopamine neurons to
the same stimuli that encode reward value (Morris et al., 2004).
These coordinated systems modulate the timing of reinforcement
learning in the striatum and thus shape the behavioral output of the
basal ganglia (Apicella, 2007).
The mechanisms underlying the responses of cholinergic
interneurons to motivationally salient stimuli are unclear.
GABAergic inputs from MSNs (Gonzales et al., 2013) could
initiate the pause, but physiological evidence for such a connection is lacking. Therefore, GABAergic interneurons have also
been implicated (Sullivan et al., 2008). Furthermore, the intrinsic
membrane properties and autonomous firing of cholinergic neurons mean that a brief barrage of synaptic excitation can produce
complex changes in their firing patterns, including pauses in continuous firing (Oswald et al., 2009; Ding et al., 2010). Both ana-
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
3102 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
tomical (Lapper and Bolam, 1992) and physiological (Ding et al.,
2010; Threlfell et al., 2012) evidence suggests that a major source
of this synaptic excitation are the projections from the intralaminar thalamic nuclei (ITN). Indeed, thalamic input appears necessary for the pause response of TANs in nonhuman primates
(Matsumoto et al., 2001). In vivo, electrical stimulation of cortex
has also been shown to excite cholinergic interneurons at short
latencies, suggesting a monosynaptic connection (Reynolds and
Wickens, 2004; Sharott et al., 2012), but there is little anatomical
evidence to suggest direct cortical innervation (Lapper and Bolam, 1992; Dimova et al., 1993).
In this study, we demonstrate that the same cholinergic interneuron can form synapses with both cortical and thalamic afferents and
that driving these excitatory synapses can lead to distinctive effects
on interneuron firing properties. The magnitude of the initial excitation in these interneurons predicts the temporal profile of the subsequent response components. Finally, we show that this correlation
between initial excitation and the profile of the multiphasic response
is present in TANs responding to specific motivationally relevant
stimuli in behaving primates.
Materials and Methods
Electrophysiological recordings in rats
Experimental procedures were performed on adult male Sprague Dawley
rats (Charles River Laboratories) and were conducted in accordance with
the Animals (Scientific Procedures) Act of 1986 (United Kingdom) and
with Society for Neuroscience Policies on the Use of Animals in Neuroscience Research.
Recording and labeling experiments were performed in 27 anesthetized rats (280 –340 g). Briefly, anesthesia was induced with 4% v/v isoflurane in O2, and maintained with urethane (1.3 g/kg ethyl carbamate,
i.p.; Sigma-Aldrich) and supplemental doses of ketamine (30 mg/kg Ketaset, i.p.; Willows Francis) and xylazine (3 mg/kg Rompun, i.p.; Bayer),
as described previously (Magill et al., 2006; Sharott et al., 2012). Wound
margins were infiltrated with local anesthetic (0.5% w/v bupivacaine;
AstraZeneca). Animals were then placed in a stereotaxic frame (Kopf).
Body temperature was maintained at 37 ⫾ 0.5°C with a homoeothermic
heating device (Harvard Apparatus). Electrocorticogram (ECoG) readings, electrocardiographic activity, and respiration rate were monitored
constantly to ensure the animals’ wellbeing. The epidural ECoG was
recorded above the frontal (somatic sensory-motor) cortex (4.2 mm
anterior and 2.0 mm lateral of bregma; Paxinos and Watson, 1986) and
was referenced against the ipsilateral cerebellar hemisphere (Mallet et al.,
2008). Raw ECoG was band-pass filtered (0.3–1500 Hz, ⫺3 dB limits)
and amplified (2000⫻; DPA-2FS filter/amplifier; NPI Electronic) before
acquisition. Extracellular recordings of the action potentials (“spikes”) of
individual neurons (i.e., single-unit activities) in the dorsal striatum were
made using glass electrodes (10 –30 M⍀ in situ; tip diameter ⬃1.2 ␮m)
containing 0.5 M NaCl solution and neurobiotin (NB; 1.5% w/v; Vector
Laboratories). Electrodes were lowered into the brain under stereotaxic
guidance and using a computer-controlled stepper motor (IVM-1000;
Scientifica) that allowed the electrode depth to be determined with a
resolution of 0.1 ␮m. Electrode signals were amplified 10 times through
the bridge circuitry of an Axoprobe-1A amplifier (Molecular Devices),
AC coupled, amplified another 100 times, and band-pass filtered at 300 –
5000 Hz (DPA-2FS filter/amplifier). The ECoG and single-unit activity
were each sampled at 16.6 kHz using a Power1401 analog-digital converter and a PC running Spike2 acquisition and analysis software (Version 7.2; Cambridge Electronic Design). After electrophysiological
recordings, single neurons were juxtacellularly labeled with NB (Magill et
al., 2000). Briefly, positive current pulses (2–10 nA, 200 ms, 50% duty
cycle) were applied until the single-unit activity became robustly entrained by the current injections. After the recording and labeling sessions, the animals were given a lethal dose of ketamine (150 mg/kg) and
were perfused transcardially with 100 ml of 0.05 M PBS, pH 7.4, followed
by 300 ml of 0.1% w/v glutaraldehyde and 4% w/v paraformaldehyde in
0.1 M phosphate buffer, pH 7.4 (PB), and then by 200 ml of 4% w/v
paraformaldehyde in PB. Brains were then left in the latter fixative solution at 4°C until sectioning 24 –72 h later.
Electrical stimulation of the cortex and thalamus. Parallel, bipolar stimulating electrodes (constructed from nylon-coated stainless steel wires;
California Fine Wire) with tip diameters of ⬃100 ␮m, a tip separation of
⬃150 ␮m, and an impedance of ⬃10 k⍀ were implanted into the ipsilateral frontal cortex (Magill et al., 2004) and ipsilateral intralaminar
thalamus. The coordinates of the cortical stimulation sites (2.5– 4.0 mm
anterior and 2.5–3.0 mm lateral of bregma, at depths of 2.0 –2.2 mm
below the dura) correspond to layers 5/6 of the primary/secondary motor
cortices (Paxinos and Watson, 1986). For thalamic stimulation, we used
coordinates (3.7 mm posterior and 1.3 mm lateral of bregma, at depths of
5.4 –5.7 mm below the dura) that consistently led to an electrode track in
the parafascicular nucleus (Pfn). Electrical stimuli, which consisted of
square-wave current pulses of 0.3 ms duration and variable amplitude
(100 –900 ␮A), were delivered using a constant-current isolator (A360D;
World Precision Instruments) that was gated by digital outputs from the
Power1401 converter. Different stimulation protocols were applied to
cortex and then thalamus or vice versa depending on the response of the
individual neuron: (1) a single-pulse stimulation delivered to cortex/
thalamus, (2) a paired-pulse stimulus given with a 100 ms interstimulus
interval, and (3) a train of 5 stimuli given with a 25 ms interstimulus
interval. Regardless of the type of stimulation (single, paired, or 40 Hz
train), each was given at 2 s intervals.
Tissue processing for identification of recorded and labeled neurons. Parasagittal sections (50 ␮m) were cut from each brain using a vibrating
microtome (VT1000S; Leica Microsystems), collected in series, and
washed in PBS. Free-floating sections were then incubated overnight at
room temperature in Triton PBS (PBS containing 0.3% v/v Triton
X-100; Sigma-Aldrich) containing Cy3-conjugated streptavidin (1:1000
dilution; Life Technologies). Sections containing NB-labeled neuronal
somata (those marked with Cy3) were then isolated for molecular characterization by indirect immunofluorescence (Sharott et al., 2012). Neurons with densely spiny higher-order dendrites were classified as
projection neurons (MSNs) and were thus not tested for interneuron
markers. Aspiny neurons were tested for expression of immunoreactivity
for choline acetyltransferase (ChAT). Briefly, after 1–2 h of incubation in
Triton PBS containing 10% v/v normal donkey serum (NDS; Jackson
ImmunoResearch Laboratories), sections containing NB-labeled neuronal somata were incubated in Triton PBS containing 2% v/v NDS and a
primary antibody against ChAT overnight at room temperature (goatanti-ChAT, catalog # AB144P, 1:500; Millipore Bioscience Research Reagents). A fluorescent secondary antibody was then applied (Alexa Fluor
488; donkey-anti-goat; 1:000; Jackson ImmunoResearch) for ⬃4 h. Only
NB-labeled neurons expressing ChAT were included in this study. To
determine the placement of the thalamic stimulating electrode, an antibody against cerebellin 1 (rabbit anti-CBLN 1, 1:3000; a gift from J.
Morgan, St. Jude Children’s Research Hospital) with heat pretreatment
as a means of antigen retrieval (Jiao et al., 1999) was used on sections in
which the electrode track was apparent. Cerebellin 1 is a selective marker
of the Pfn compared with neighboring structures (Kusnoor et al., 2010);
in some cases, this was combined with Nissl staining to delineate the
thalamic nuclei (NeuroTrace, catalog #N21479, 1:100; Invitrogen). Judging from the robust responses of interneurons that we obtained and the
anatomical verifications, it is likely that both poles of the stimulating
electrodes were located in, or very close to, the Pfn. Despite this, we
cannot rule out the possibility that the evoked electric field was not
confined to the Pfn, so we conservatively refer to stimulation as being
“thalamic.”
Electron microscopy
Immunohistochemistry. Four recorded and labeled cholinergic interneurons from four rats were processed for electron microscopy (EM). The
first neuron was a pilot study to establish the immunohistochemical and
electron microscopic protocols. The four neurons used for EM analysis
were positive for ChAT. Sections containing neuronal processes (lateral
and medial to the section containing the soma) were isolated for EM
processing. Sections were incubated in cryoprotectant (25% sucrose,
10% glycerol) overnight at 4°C. Sections (one at a time) were then freeze
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
thawed using liquid nitrogen. Each section was laid flat in one well of a
six-well plate and excess cryoprotectant was removed using filter paper.
The well plate was then lowered over liquid nitrogen until the section
froze and went opaque. The section was then rapidly thawed using cryoprotectant that had been kept at room temperature. The sections were
then incubated in cryoprotectant for at least 1 h at room temperature or
until all sections had sunk to the bottom of the glass vial. The freezing
process was then repeated for all of the sections and the sections were
thawed with room temperature 0.1 M PB. All of the sections were then
washed in 0.1 M PB twice and three times in PBS and incubated in PBS
containing 10% NDS for 1 h at room temperature on a shaker. The
sections were then incubated in avidin-biotin-peroxidase complex
(ABC, 1:250; Vector Labs) prepared according to the manufacturer’s
instructions in a 1% NDS PBS solution.
After incubation in ABC, the sections were washed 3 times in PBS,
followed by 3 washes in 0.1 M PB, pH 6.0. A peroxidase reaction using
tetramethylbenzidine (TMB) as the chromogen was then performed to
reveal the NB-filled neuron (Doig et al., 2010). Sections were placed for
20 min in a preincubation solution containing the following: 80 ml of 0.1
M PB, pH 6.0, 4 ml of ammonium paratungstate (1% in deionized H2O),
1 ml of TMB (catalog # T5525, 0.2% dissolved in absolute ethanol;
Sigma-Aldrich), 800 ␮l of ammonium chloride (0.4% in deionized
H2O), and 800 ␮l of D-glucose (20% in deionized H2O). To perform the
reaction, the preincubation solution was removed and replaced with the
reaction solution, which consisted of 2 ml of the preincubation solution
(as above) plus 2 ␮l of glucose oxidase (catalog #G6891; Sigma-Aldrich).
The reaction was initially performed on the section containing the cell
body to gauge the optimum processing time; the section was wet
mounted and checked under a light microscope (40⫻). The reaction was
then allowed to progress for all sections for between 6 and 8 min depending on the neuron. The reaction was stopped with 0.1 M PB, pH 6.0.
Sections were then washed 3 times for 5 min with 0.1 M PB, pH 6.0. The
reaction was then stabilized by incubation in a solution containing the
following: 400 ␮l of ammonium chloride (0.4% in deionized H2O), 400
␮l of D-glucose (20% in deionized H2O), 800 ␮l of cobalt (II) chloride
(1% in deionized H2O), and 40 mg of DAB dissolved in 40 ml of 0.1 M PB,
pH 6.0. The stabilization solution was filtered before use. Sections were
incubated for 15 min at room temperature. The stabilization solution
was then removed and replaced with 3 10 min washes of 0.1 M PB, pH 6.0.
During stabilization, the blue-staining color from the reaction step
changes to a darker magenta color and background staining is reduced.
Sections were then washed 3 times in 0.1 M PB, pH 7.4.
Alternate sections were then processed to reveal either VGluT1 or
VGluT2 labeling using the peroxidase-anti-peroxidase (PAP) method
(Bolam, 1992). Alternate sections were incubated in a primary antibody
against either VGluT1 (rabbit-anti-VGluT1, catalog #VGT3, 1:2000;
MAb Tech) or VGluT2 (rabbit-anti-VGluT2, catalog #, 135403, 1:2000;
Synaptic Systems) overnight at room temperature in PBS. The sections
were then incubated in an un-conjugated antibody (donkey-anti-rabbit
IgG, catalog #711-035-152, 1:100; Jackson ImmunoResearch) for at least
4 h at room temperature. Next, the sections were incubated in a PAP
complex (rabbit PAP, catalog #323-005-024, 1:400; Jackson ImmunoResearch) for at least 4 h at room temperature. A peroxidase reaction using
DAB as the chromogen was used to reveal VGluT1 or VGlut2 labeling.
Sections were incubated in a solution containing DAB (0.05%) dissolved
in TRIS buffer for 20 min. Hydrogen peroxidase (H2O2) was then added
to the solution to achieve a final concentration of 0.01%. The reaction
was monitored using a dissection microscope. All sections were incubated for between 3 and 4 min. They were then washed in Tris buffer 3
times, followed by 3 washes in 0.1 M PB, pH 7.4.
Sections were then post-fixed in osmium tetroxide (1% w/v in PB;
Oxkem) for 25 min and then washed in 0.1 M PB and dehydrated in an
ascending series of ethanol dilutions as follows: 15 min in 50% w/v ethanol, 35 min in 70% ethanol that included 1% w/v uranyl acetate, 15 min
in 95% ethanol, and twice for 15 min in absolute ethanol. After absolute
ethanol, sections were washed twice in propylene oxide (Sigma-Aldrich)
for 15 min and placed into resin (Durcupan ACM; Fluka) and left overnight at room temperature. Sections were then placed on microscope
slides, a coverslip was applied, and the resin was cured at 65°C for ⬃72 h.
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3103
Reconstruction and ultrathin sectioning. The 3D reconstruction of NBlabeled neurons was performed using Neurolucida (MBF) using an oilimmersion objective (60⫻). The tracings within the separate sections
were then spliced using Neurolucida and the final version was corrected
for shrinkage in all dimensions: x (6.3%), y (6.0%), and z (8%; Sadek et
al., 2007). A file with the entire neuron unspliced was saved to be used as
a guide for resectioning dendritic fragments. Quantitative data from the
reconstructions was then obtained using Neuroexplorer (MBF). For the
Sholl analysis, radius segments of 50 ␮m were used. The data were then
exported to Microsoft Excel (2007).
Light microscopic images of the dendrites of each neuron (20⫻) were
aligned with the reconstruction to identify specific dendritic fragments in
each sagittal section. At least one dendritic fragment was reembedded
from each sagittal section from the “top” of the section. Ultrathin sections (50 nm) containing the pieces of dendrite were then resectioned
using an ultramicrotome (EM UC6; Leica Microsystems) and collected
on pioloform-coated single slot grids. The sections were then contrasted
using lead citrate.
Electron microscopy and analysis. The dendritic fragment(s) within
each ultrathin section was then imaged using an electron microscope
(CM10; Philips) at a high magnification (13,500⫻ to 46,000⫻). Each
dendritic fragment was analyzed through several grids and in serial section on each grid, with a minimum of five sections analyzed per grid. The
major factor limiting the extent of dendrite that could be analyzed was
the penetration of the VGluT antibodies. To control for the possibility of
VGluT-false-negative terminals, serial sections on a grid were only examined if there was at least one VGluT1/2-positive profile present in one of
the sections on the grid (at a magnification of at least 13,500⫻).
Electron micrographs were then analyzed using ImageJ software (Version 1.41o). Every synapse formed with the sections of dendrites examined was analyzed and every presynaptic terminal forming a symmetric
(type II) or an asymmetric (type I) synapse with the labeled dendrite was
recorded. The length of the postsynaptic density for every synapse
formed with the cholinergic dendrite was measured. Synaptic density was
calculated as the number of synapses divided by the length of dendrite (in
micrometers) examined (in the z-axis, from the number of ultrathin
sections analyzed) and then expressed as density per 10 ␮m.
Estimations of the total number of synapses onto the dendrites of
cholinergic interneurons were calculated as follows, based on data acquired. To estimate the total number of synapses, the average height
examined for each section was calculated based on the number of ultrathin sections examined and the number of synapses found within that
height was obtained from the data. For example, for neuron NJX009, the
average height per section examined was 2.12 ␮m (out of a potential 45
␮m of section thickness) and a total of 90 synapses (symmetric, asymmetric, and VGluT2 positive) were counted within this thickness. The
number of synapses was then multiplied by a correction factor to estimate the total number of synapses as if the entire height of the section was
analyzed. For NJX009, there were 12 sections, each with a thickness of 45
␮m (after shrinkage), so the number of synapses (90) was thus multiplied
by 20.2 (⫽1818.13). The total number of high endings of dendrite for
each neuron was counted from the unspliced Neurolucida files. For
NJX009, a possible total of 78 high endings could have been sampled and,
out of this, 20 were examined. A correction factor was then used to
estimate what the number of synapses would be had every high ending
been sampled. In the case of NJX009, this correction factor was 3.9, so the
predicted number of synapses for NJX009 is 7090.70 (1818.13*3.9). This
method is based on the protocol established by Henny et al. (2012, 2013).
We chose to use this method because it is based entirely on the EM
ultrastructural data and does not take into account dendritic length,
which decreases the error, for the following reasons: (1) the dendritic
length would be estimated from the Neurolucida files (and not the ultrathin sections) and (2) by using this method, the orientation of the dendrite within the section is not incorporated. The method was then
repeated to estimate the total number of symmetric, asymmetric, and
VGluT1 or VGluT2 synapses for each neuron. Numbers of VGluT1 and
VGluT2 synapses were doubled to take into account the fact that the
sampling was only performed in one of two series.
3104 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
Electrophysiological recordings of TANs in behaving primates
Single neurons were recorded from the striatum of four behaving macaque monkeys (identified as C, P, G, and B). The monkeys were seated in
a restraining box that was described previously (Apicella et al., 1997) and
faced a panel placed ⬃30 cm in front of them. Each was chronically fitted
with a head-restraining device and a recording chamber over a craniotomy for electrode insertions mainly targeted at the putamen. Surgical
and electrophysiological procedures were as described previously (Apicella et al., 1997). Monkey surgery and behavioral testing protocols were
in accordance with guidelines set by the National Institutes of Health and
the French government regulations on animal experimentation. Neurons were accessed on vertical penetrations with glass-coated tungsten
electrodes. The electrodes were advanced with a hydraulic microdrive
(MO-95; Narishige) through a stainless steel guide tube that was used to
penetrate the dura. Signals from neuronal activity were conventionally
amplified, filtered (band pass, 0.3–1.5 kHz), and converted to digital
pulses through a window discriminator. Putative cholinergic interneurons (TANs) were classified according to their electrophysiological characteristics, as described previously (Aosaki et al., 1994), as well as their
typical responses to unexpected rewarding stimuli (Apicella et al., 1997).
Our focus on TANs recorded in putamen was not only in keeping with
many other past studies of salience-/reward-related TAN activity in behaving primates (Aosaki et al., 1994; Apicella et al., 1997; Morris et al.,
2004), but also allowed for the most direct comparison (in terms of
broadly equivalent circuits and function) with our sample of rat cholinergic interneurons. Although there is some regional bias in the responses
of primate striatal neurons to salient/rewarding stimuli, uniformity in
TAN responses across the striatal axis has been commonly emphasized
(Morris et al., 2004; Adler et al., 2013a; Adler et al., 2013b).
The activity of TANs were studied with respect to two behavioral
conditions. In the first condition, a Pavlovian protocol in which the onset
of a visual stimulus on the center of the panel at unpredicted times was
followed, after a 1 s delay, by the delivery of liquid reward (0.3 ml of apple
juice) via a tube positioned directly in front of the monkey’s mouth. All
monkeys were highly experienced with the associative relationship between stimulus and reward; that is, the monkey used the stimulus as a
predictor of the upcoming reward, as reflected by licking movements
starting before reward delivery. We will refer to this situation as the
reward-predicting stimulus condition. In the second condition, the same
liquid reward was repeatedly delivered at irregular time intervals (5.5–
8.5 s) in the absence of any predictive stimulus. We will refer to this
situation as the reward-only condition. The two conditions were presented as separate blocks of 30 – 40 trials each, the order of blocks being
chosen randomly. In our previous work, we have demonstrated that the
TAN response to a stimulus that predicts reward is paralleled by a lack of
responsiveness to the reward itself (after Pavlovian conditioning),
whereas most TANs remain responsive to unexpected deliveries of reward outside of any task (for review, see Apicella, 2007).
Our database consisted of 79 TANs recorded in the reward-predicting
stimulus condition (26 from C, 25 from P, and 28 from G) and 130 TANs
recorded in the reward-only condition (23 from C, 10 from G, and 97 from
B). Eleven TANs were recorded in both conditions. The behavioral situations, recording methods, and TAN responses properties have been described previously (Ravel et al., 2003; Apicella et al., 2011; Deffains et al.,
2010).
Data analysis
Analysis of short-latency responses of rat cholinergic interneurons to afferent
stimulation. Peristimulus time histograms (PSTHs) were constructed
from 50 –200 consecutive stimulation trials with 2 ms bins and normalized to give firing probability (spikes per bin/trials). Cholinergic interneurons were considered to respond significantly at “short latency” if
ⱖ20% of first spikes after the stimulus were fired in a response window of
1.5–20 ms and if, within this window, there was a histogram peak ⬎3 SDs
of the prestimulus (“baseline”) firing probability (defined from ⫺400 to
⫺100 ms before stimulation at 0 ms). Neurons were considered to respond significantly at “long latency” if 20% of first spikes after the stimulus were fired in a response window of 20 –50 ms and if there was a peak
⬎3 SDs of the baseline in this window. The first spike in each stimulus
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
trial, rather than the peak of the response in the PSTH, was therefore used
to measure the response latency. The mean latencies of the first spikes in
a given time window were compared using a Mann–Whitney U test or
Wilcoxon signed-rank test as appropriate. The same short-latency analysis windows were also used for both paired-pulse and high-frequency
train stimulation. For paired-pulse stimulation, latencies and firing
probabilities across the first and second pulse were compared using Wilcoxon signed-rank tests as long as there were ⱖ5 spikes in this window in
response to both pulses. Because our high-frequency stimulation cycle was at
40 Hz, we were able to perform the same analysis as for single stimulation
within each 25 ms interval of the high-frequency stimulation pulse. Mean
latency and firing probability were therefore calculated for each of the five
pulses in the stimulation train. The cumulative sum of the firing probability
across the five pulses and its slope was calculated to measure the magnitude
of accumulated spiking through the stimulus train.
Characterization of multiphasic responses of rats and primate neurons
using PSTHs. We designed a unified framework to characterize the multiphasic responses of both identified rat cholinergic interneurons to
cortical/thalamic stimulation in anesthetized rats and of TANs to behaviorally relevant stimuli (reward-predicting cues or reward delivery with
no cue) in monkeys. This involved a two-step approach in which we first
calculated the overall temporal profile and established the class of response (any combination of initial excitation/pause/rebound) of each
neuron based on its PSTH and then used this information to calculate
parameters of the three phases for each trial.
First, a smoothed PSTH (50 ms bins with 90% overlap) was computed
to define the response phases. After these PSTHs were normalized as a
percentage of baseline firing, peaks and troughs were detected using a
threshold of five contiguous bins over or under the 95% confidence
interval of the 400 ms prestimulus baseline firing in the PSTH (from
⫺450 to ⫺50 ms for rats, from ⫺500 to ⫺100 ms for monkeys). In both
the rat and monkey datasets, the most elaborate population responses
included early increases in firing rate (from here on defined as an “initial
excitation”), followed by a decrease in or cessation of firing (“pause”),
followed by a renewed increase in firing (“rebound”), as described previously (Schulz and Reynolds, 2013). Significant peaks and troughs in
PSTHs were thus assigned to initial excitation, pause, and/or rebound
phases based on their latencies compared with the population response
and these previous investigations. For single-pulse stimulation in rats,
the temporal boundaries of the response phases were as follows: initial
excitation: 1–50 ms; pause: 50 – 400 ms; and rebound: 200 –700 ms. For
high-frequency train stimulation in rats, the boundaries were as follows:
initial excitation: 1–150 ms (after the first pulse in the train); pause:
50 – 400 ms; and rebound: 200 –700 ms. Therefore, for responses evoked
by high-frequency electrical stimulation, the phase of initial excitation
encompassed all spiking after the first pulse up until 25 ms after the last
pulse. For primate TAN responses to behaviorally relevant stimuli, the
boundaries were as follows: initial excitation: 10 –200 ms (after the
reward-predicting stimulus or reward delivery); pause: 75–350 ms; and
rebound: 200 –700 ms. Note that the windows for the three phases are
wide and overlapping to allow for variations in the temporal profile
across neurons and jitter in the response latencies. Significant responses
were defined as such when they were detected at any time within these
boundaries. This is particularly relevant for the primate data in which the
latencies for each phase were longer for the reward-only condition. Based
on the combination of peaks and troughs displayed, neurons responses
were assigned to one of eight categories: Unclassified, Initial excitation
only, Pause only, Rebound only, Initial excitation/Pause, Initial excitation/
Pause/Rebound, Initial excitation/Rebound, and Pause/Rebound. The
smoothed PSTHs were also used to define the start and end of each response
phase. Every PSTH was extensively scrutinized to verify that these boundaries and other criteria led to satisfactory response classification.
Trial-by-trial analysis of multiphasic responses of neurons in rats and
primates. Having defined the response class and the timing of each PSTH
response phase for each neuron in rat and monkey, we used these data to
analyze the relationship between the different response phases on a trialby-trial basis. The PSTH response classification allowed us to establish
that the majority of rat and monkey neurons displayed a pause (see
Results). Therefore, for each neuron that had a pause in the PSTH, we
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
used the pause onset, defined by the first bin in the PSTH that fell below
the 95% confidence interval, as a reference point to calculate a value
for the number of spikes in the preceding initial excitation, the duration
of the pause itself, and the change in firing rate during the subsequent
rebound phase for every stimulus trial.
Initial excitation. This initial excitation phase for each trial was defined
as the number of spikes fired between the “trigger” (the first electrical
stimulation in rat data or the visual cue or reward delivery in primate
data) and 50 ms after the start of the pause onset (to allow for single trials
in which the initial excitation lasted longer that the PSTH pause onset) as
defined by the PSTH. Trials could then be separated based on how many
spikes were fired in this initial excitation phase and PSTHs recalculated to
include only the trials with a given number of spikes in this window. For
group statistics, the number of spikes in each trial was averaged for each
individual rat cholinergic interneuron or primate TAN.
Pause. The pause phase for each trial was defined as the interspike
interval between the last spike of the initial excitation phase and the next
spike. For trials in which no spikes were fired in the initial excitation
window (i.e., no activity up to 50 ms after the start of the PSTH pause),
the start of the pause for that trial was the start of the PSTH pause (i.e., the
first bin in the PSTH to be significantly below the baseline). The individual pause values for each trial were normalized by the mean interspike
interval of the baseline period for the entire set of trials (Ding et al., 2010).
For group statistics, the mean pause for each neuron was the mean pause/
trial divided by the mean interspike interval during baseline firing.
Therefore, a value of ⬎1 indicates that the pause interval is greater than
the mean interspike interval of the baseline.
Rebound. The rebound phase for each trial was defined as the firing
rate in the 500 ms after the pause interval for that trial (including the
spike that defined the pause offset) normalized by the mean firing rate of
the baseline period. Therefore, the “rebound rate” was the percentage
change in the firing rate of the 500 ms after the pause compared with the
baseline rate.
This trial-by-trial approach had several advantages compared with
analyzing responses based on the PSTH. First, the calculation of these
values was not directly dependent on the binning of data for the PSTH.
Second, in the cases for which there was no initial excitation or rebound
peak in the PSTH, it was still possible to calculate the values for these
response phases and to detect single trials that did have increases in
spiking during these phases. Third, by defining values for each response
phase in each trial, we could isolate and sort trials based on specific
characteristics (e.g., one, two, or three spikes in the initial excitation
phase/sorting trials by pause length). Finally, using these methods enabled us to focus our analyses on changes in firing rate within a trial, not
consistency in latency with respect to the stimulus across trials. Such
changes are less dependent on binning and likely to be more relevant to
the online computation performed by the neuron. In summary, our
analyses enabled us to investigate, within the same analytical framework,
the multiphasic responses of both rat cholinergic interneurons after electrical stimulation and monkey TANs after rewarding stimuli.
Results
Cortical and thalamic inputs to individual cholinergic
interneurons in the rat
Although cholinergic interneurons only make up a small proportion of striatal neurons, it is widely accepted that these interneurons play an important role in reward-related behavior through
the modulatory actions of the acetylcholine that they release
within the striatum. In the first part of this study, cholinergic
interneurons were recorded in the striatum of anesthetized rats.
Online identification of putative cholinergic interneurons was
facilitated by previous work in urethane-anesthetized rats (Sharott et al., 2012) showing that, regardless of brain state, cholinergic interneurons fire spontaneously at similar rates (3– 6 Hz;
Fig. 1A). After the recording of spontaneous activity, the same
interneurons were then recorded during the delivery (in random
order) of a variety of electrical stimuli to the cortex (ipsilateral
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3105
motor cortex) and/or thalamus (nominally targeted to ipsilateral
parafascicular nucleus). An individual cholinergic interneuron
could fire at short latencies (⬍20 ms) in response to single-pulse
stimulation of both cortical and thalamic sites (Fig. 1 B, C). The
interneuron shown in Figure 1 responded to cortical stimulation
with an average delay to first spike of 9.1 ms (Fig. 1B) and to
thalamic stimulation with an average delay of 12.7 ms (Fig. 1C).
These and similar short-latency excitation responses were assumed to reflect activation of monosynaptic inputs. Note, however, that the responses of interneurons to single-pulse afferent
stimulation were often multiphasic. Therefore, short-latency excitations were often followed by (in order) a cessation of firing and a
subsequent rebound increase in firing (Fig. 1B,C). After recording
and electrical stimulation, interneurons were juxtacellularly labeled
with NB (Fig. 1D) and subsequently tested for the expression of
ChAT immunoreactivity (Fig. 1E). All rat neurons included in this
study were confirmed to express ChAT and were thus unequivocally
identified as cholinergic interneurons.
The synaptic innervation of three physiologically and neurochemically characterized cholinergic interneurons was examined
at the EM level. The somata and dendrites of these cholinergic
interneurons were first digitally reconstructed in 3D (Fig. 1F ).
Alternate tissue sections were incubated in antibodies against either vesicular glutamate transporter 1 or 2 (VGluT1 or VGluT2)
to quantify inputs from cortex and thalamus, respectively (Doig et
al., 2010; Henny et al., 2012; Henny et al., 2013) and then processed
for EM. One identified cholinergic interneuron (#AJS044) that exhibited robust responses to cortical and thalamic stimulation in vivo
(the same neuron as shown throughout Fig. 1) was shown to form
synapses with axons originating in both the cortex (VGluT1 positive;
Fig. 1G) and the thalamus (VGluT2 positive; Fig. 1H). This establishes the precedent that an individual cholinergic interneuron can
form synapses with axon terminals arising from both the cortex and
thalamus. Further details of the synaptic innervation of cholinergic
interneurons are discussed below.
Synaptic innervation of cholinergic interneurons
A detailed anatomical examination of the synaptic inputs to three
identified cholinergic interneurons was performed using EM.
The NB-filled neurons were first reconstructed in 3D before reembedding and resectioning for EM (Henny et al., 2012; Henny
et al., 2013). In agreement with previous studies, cholinergic interneurons had distinctly large cell bodies, and between three and six
primary dendrites that extend in a radial pattern from the soma for
up to ⬃700 ␮m (e.g., Fig. 1F; Wilson et al., 1990; Inokawa et al.,
2010; Sharott et al., 2012). The average total dendritic length for the
three neurons reconstructed was 9411 ␮m (⫾ 511).
After reconstruction, fragments of dendrites from all parts of
the dendritic arbor were sectioned for analysis in the electron
microscope. For each neuron, serial sections of 20 –24 dendritic
fragments were examined in tissue labeled for either VGluT1 or
VGluT2 (Table 1). Dendritic fragments were examined in serial
sections in tissue that exhibited staining for VGluT1 or VGluT2.
On average, 42 sections were analyzed for each of the dendritic
fragments, giving an overall average of 892 sections per neuron
(Table 1). All terminals forming synapses with the dendrites were
noted (Fig. 2, Table 1) and categorized as follows: (1) DABnegative (unlabeled) terminals forming asymmetric (Gray’s type
I) synapses (Fig. 2A–C, Table 1); (2) DAB-negative (unlabeled)
terminals forming symmetric (Gray’s type II) synapses (Fig. 2D,
Table 1); and (3) DAB-positive (i.e., VGluT1-or VGluT2immunopositive) terminals forming asymmetric synapses (Figs.
1 E, F, 2B, Table 1).
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
3106 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
Table 1. EM analysis of the synaptic innervation of cholinergic interneuron
dendrites
Neurons
Properties examined
NJX009 AJS044 NJX014 Average
Total number of ultrathin sections examined (50 nm) 849
Total number of dendritic fragments analyzed
20
In VGluT1-labeled tissue
11
In VGluT2-labeled tissue
9
Total number of unlabeled (DAB-negative)
23
asymmetric synapses
In VGluT1-labeled tissue
11
In VGluT2-labeled tissue
12
Total number of VGluT1-positive synapses
0
Total number of VGluT2-positive synapses
6
Total number of (unlabeled) symmetric synapses
61
1039
24
14
10
32
789
20
11
9
46
892.33
21.33
12.00
9.33
33.67
22
10
2
5
62
27
19
0
3
64
20.00
13.67
0.67
4.67
62.33
For each neuron examined, several properties were analyzed over a number of sections in either VGluT1- or VGluT2labeled tissue.
Overall, 62% of the terminals in contact with the dendrites of
cholinergic interneurons formed symmetric synapses (Fig. 2E)
and 38% formed asymmetric synapses ( p ⫽ 0.05; Mann–Whitney U test, two-tailed, Fig. 2E). Of the terminals that formed
asymmetric synapses, 1.7% were positive for VGluT1 and 13%
for VGluT2 (Fig. 2E, inset). The remainder of terminals forming
asymmetric synapses were DAB negative in tissue labeled for either VGluT1 (49.8 ⫾ 3.4%) or VGluT2 (35.3 ⫾ 2.8%; Fig. 2E,
inset). Therefore, the predominant type of synapse formed with
the dendrites of cholinergic interneurons was symmetric and
formed by unlabeled terminals.
We then examined the distribution of synapses formed with
the cholinergic neurons in different parts of the dendritic arbor
(Fig. 2F, Table 2). Dendrites were defined as “proximal” to the
soma (i.e., within the first 20% of the total length from the soma
of the longest dendrite; Henny et al., 2012; Henny et al., 2013),
“distal” (21– 80%); or “most distal” (the farthest 20% of the distance of dendrites from the soma; Table 2). The number and type
of terminals forming synapses was examined within each compartment (Table 2). The number of terminals forming asymmetric or symmetric synapses was normalized based on the length of
dendrite within each compartment for each dendritic fragment
(Fig. 2F ). Of the two terminals positive for VGluT1, one was on a
proximal dendrite and the other on a distal dendrite (Table 2).
Synapses formed by terminals positive for VGluT2 were found in
all dendritic compartments (Table 2).
Overall, the average density of terminals forming asymmetric
synapses per 10 ␮m of dendrite was 9.9 ⫾ 1.1 compared with
14.4 ⫾ 1.2 symmetric synapses; therefore, over the entire dendritic tree, the density of symmetric synapses was significantly
greater than the density of asymmetric synapses (p ⫽ 0.0038; Mann–
Whitney U test, two-tailed). This ratio of symmetric to asymmetric
synapses is in agreement with previous data (Sizemore et al., 2010).
Indeed, in all compartments, there were more terminals forming
4
Figure 1. Individual identified cholinergic interneurons can respond to cortical and thalamic
stimulation and receive synaptic input from the cortex and the thalamus. A, Recording of the
spontaneous spike firing of an individual cholinergic interneuron (#AJS044) in an anesthetized
rat; vertical scale bars, 1 mV; horizontal scale bar, 1 s. B, Raster plot (top) and PSTH (bottom)
showing the response of interneuron in A to single-pulse stimulation of ipsilateral motor cortex.
A single-trial example of an evoked spike waveform after cortical stimulation (arrow) is inset;
horizontal scale bar, 5 ms; vertical scale bar, 1 mV. C, Raster plot (top) and corresponding PSTH
(bottom) showing the response of the same interneuron to single-pulse stimulation (arrow) of
the ipsilateral thalamus (targeted to the parafascicular nucleus). An example of an evoked spike
waveform after thalamic stimulation is inset; horizontal scale bar, 5 ms; vertical scale bar, 1 mV.
Note the short-latency excitations (⬍20 ms) and multiphasic responses evoked by cortical and
thalamic stimuli. D, E, After recording, the same interneuron was juxtacellularly labeled with NB
and tested positive for immunoreactivity against ChAT, thus confirming its cholinergic identity.
Scale bars, 25 ␮m. F, Somata and dendrites of the identified cholinergic neuron digitally reconstructed in 3D. Scale bar, 25 ␮m. G, H, The same interneuron was then examined using electron
microscopy. In G, a dendrite (d) is shown forming an asymmetric synapse (arrowhead) with an
axon terminal (white asterisk) that is positive for VGluT1, a marker of cortical terminals. Note
the crystalline deposits in the dendrite formed by the TMB. Scale bar, 0.25 ␮m. In H, another
dendrite (d) is shown forming an asymmetric synapse (arrowhead) with an axon terminal
(white asterisk) that is positive for VGluT2, a marker of thalamic terminals.
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3107
symmetric than asymmetric synapses; however, this was most prominent proximal to
the soma, with asymmetric synapses forming 8.6 ⫾ 1.1 synapses per 10 ␮m of dendrite
and symmetric synapses forming 17.8 ⫾ 2.4
synapses, and indeed this was significant in
this proximal compartment (p ⫽ 0.0081,
Mann–Whitney U test, two-tailed; Fig. 2F).
In all other compartments, the density of
symmetric synapses was not significantly
greater than the density of asymmetric synapses (p ⬎ 0.05, Mann–Whitney U test,
two-tailed; Fig. 2F).
Due to the way in which we sampled
the synapses, we were able to extrapolate
our data and estimate the total numbers of
synapses formed with an individual cholinergic interneuron by the various different terminals. Our data suggest that an
individual cholinergic interneuron has an
average of 8450 ⫾ 694 afferent synapses in
total (Fig. 2G), of which the majority are
symmetric (an average of 5166 ⫾ 285; Fig.
2G) and the remainder are asymmetric
(an average of 2859 ⫾ 458; Fig. 2G). We
estimate that an individual cholinergic interneuron forms an average of 752 ⫾ 62
synapses with VGluT2-positive terminals.
The data also indicate that neuron AJS044
would form a total of 294 synapses with
VGluT1-positive terminals. It is clear from
these data that cholinergic interneurons
form more synapses with thalamic than cortical terminals, which is in agreement with
previous data (Lapper and Bolam, 1992).
Short-latency responses of rat
cholinergic interneurons to cortical and
thalamic stimulation
The finding that an individual cholinergic
interneuron can receive synaptic input
4
Figure 2. Terminals forming synapses with the dendrites of cholinergic interneurons. A, Example of a dendrite of a cholinergic
interneuron (d) forming an asymmetric synapse (arrowhead) with a terminal negative for VGluT1 (n). Note that there is a terminal
positive for VGluT1 (DAB product; white asterisk), forming an asymmetric synapse (arrowhead) with a MSN spine (sp). B, Cholinergic interneuron dendrite (d) forms two asymmetric synapses (arrowheads) with a VGluT2 positive terminal (asterisk) and
terminal negative for VGluT2 (n). Note that within the same frame there is another positive terminal (asterisk) forming a synapse
with an MSN spine (sp). C, A dendrite (d) forms an asymmetric
synapse (arrowhead) with a terminal negative for VGluT2 (n).
Note that the same terminal is also forming a synapse with a
spine of an MSN (sp) and that within the same frame there is a
VGluT2 positive terminal (asterisk). There is also a negative
terminal (n) forming a synapse with a spine (sp). D, The dendrite of a cholinergic interneuron (d) forms a symmetric synapse (small arrows) with an unlabeled terminal (n), see inset.
Note that within the frame there is a terminal positive for
VGluT1. Scale bars, 0.25 ␮m. E, Percentages of terminals
forming symmetric (blue) or asymmetric (green) synapses
with the dendrites examined. Of the terminals that formed
asymmetric synapses (green), some were positive for VGluT1
(red) or VGluT2 (violet). The remaining terminals were DAB
negative in tissue labeled for either VGluT1 or VGluT2 (inset).
F, Average number of asymmetric (green) and symmetric
(blue) synapses normalized for every 10 ␮m of dendrite,
within each compartment. G, Estimations of the total number
of symmetric (blue) and asymmetric (green) synapses formed
with the dendrites of cholinergic interneurons based on data
collected.
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
3108 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
Table 2. Distribution of synapses over the dendritic arbor of cholinergic interneurons
Properties examined
Proximal (0 –19%)
Distal (20 –79%)
Most distal (80 –100%)
Number of dendritic fragments analyzed
Average distance from soma (⫾SEM) (␮m)
Average distance from soma as a percentage of total distance (⫾SEM)
Ultrathin sections analyzed (total)
Average number of ultrathin sections analyzed in serial section (⫾SEM)
Total number of terminals forming asymmetric synapses
In VGluT1-labeled tissue
In VGlut2-labeled tissue
Total number of VGlut1-positive terminals forming synapses
Total number of VGlut2-positive terminals forming synapses
Total number of terminals forming symmetric synapses
17
59.96 (⫾12.19)
9.31 (⫾1.90)
730
42.94 (⫾7.02)
24
14
10
1
2
55
38
276.53 (⫾34.22)
43.64 (⫾5.40)
1568
41.26 (⫾6.26)
58
40
18
1
10
103
9
558.22 (⫾17.00)
85.48 (⫾2.17)
379
42.11 (⫾10.13)
19
6
13
0
2
29
The distribution of terminals forming synapses on dendrites at varying distances from the soma was analyzed for the three neurons examined.
from both the cortex and the thalamus concurred with the responses of these interneurons to electrical stimuli delivered to
these two regions in vivo. Thirty-two identified cholinergic interneurons were included in this study, 18 of which were recorded with cortical stimulation only; the remaining 14 were
recorded during both cortical and thalamic stimulation (delivered independently and in a random order). As a first step, the
responses of identified cholinergic interneurons to brief, singlepulse electrical stimulation of the ipsilateral motor cortex (n ⫽
32) and Pfn (n ⫽ 14) were examined (Fig. 3). Studies in vitro have
reported that excitation of either cortical or thalamic axons with
single electrical pulses does not elicit spiking responses from cholinergic interneurons (Oswald et al., 2009; Ding et al., 2010;
Schulz et al., 2011). In contrast, we found that the firing of many
cholinergic interneurons was transiently increased at “short latencies” of 1.5–20 ms in response to single-pulse stimulation of
the cortex (50% of interneurons tested) and thalamus (64%) in
vivo (Fig. 3A–F ). Short-latency decreases in interneuron firing
were not observed in response to afferent stimulation. Evoked
spiking at these short latencies is thought to be indicative of
monosynaptic inputs (Mallet et al., 2005; Sharott et al., 2012) and
likely requires many corticostriatal or thalamostriatal fibers to be
recruited by the stimulation. In vitro preparations, which entail
the loss of at least some connections, may thus not allow for the
recruitment of enough afferent neurons/axons with a singlepulse stimulus to elicit interneuron spiking.
The mean latencies of first spikes in this 1.5–20 ms window
did not significantly differ between responses to cortical (10.2 ⫾
0.49 ms) and thalamic (10.7 ⫾ 0.57 ms) stimulation (Mann–
Whitney, p ⬎ 0.05; Fig. 3G). This was also the case for individual
neurons that responded to both cortical and thalamic stimulation
(Wilcoxon signed-rank test, p ⬎ 0.05; Fig. 3H ). The majority of
cholinergic interneurons (10 of 14 tested) also responded to thalamic, but not cortical (Fig. 3 B, C, inset), stimulation at a longer
latency of 20 –50 ms (mean latency: 33.6 ⫾ 0.58 ms; Fig. 3 E, F,
inset). This later component could be due to a recruitment of
polysynaptic circuits that ultimately impinge on striatum, such as
cortical fibers that might be activated by ITN stimulation (Llinas
et al., 2002). In summary, these group data show that cholinergic
interneurons can respond with a short-latency increase in firing,
indicative of a monosynaptic drive.
In vivo, striatal projection neurons and parvalbuminexpressing (PV⫹) interneurons show distinct and opposite responses to paired-pulse stimulation (100 ms interpulse interval)
of the ipsilateral frontal cortex (Mallet et al., 2005). We next
examined the short-latency responses of cholinergic interneurons to paired-pulse stimulation (100 ms interval) of either cortex or thalamus (Fig. 4 A, B). For this protocol, we tried to apply a
stimulation current that achieved a spike response to the first
pulse around the rheobase (i.e., the current amplitude that evokes
a spike after 50% of first pulses). With paired-pulse stimulation
of cortex, cholinergic interneurons had a significantly lower
probability of short-latency firing to the second pulse (Fig. 4C), as
has been described previously for PV⫹ interneurons (Mallet et
al., 2005). Note that the short-latency response to the second
pulse decreased across the whole range of initial firing probabilities and was not therefore a phenomenon limited to an initial
high firing probability (Fig. 4C). In contrast, there was no change
in firing probability across the first and second pulses of thalamic
stimulation (Fig. 4D). Although the firing probability of the
longer-latency responses was greater after the second pulse for
some neurons (Fig. 4B), this was not significant across the population. Therefore, in a similar manner to PV⫹ interneurons,
cholinergic interneurons respond preferentially to the first pulse
in a paired-pulse stimulation protocol for cortical stimulation.
This relationship was not observed for thalamic stimulation, suggesting that: (1) electrical stimuli delivered to cortical and thalamic sites recruited distinct sets of inputs and (2) that there is a
fundamental difference in the integration of the two excitatory
afferents by cholinergic interneurons.
Previous studies, both in vitro and in vivo, have suggested that
burst-like excitatory inputs to cholinergic interneurons evoke responses that mimic the timing of these neurons to motivationally
salient stimuli in behaving animals (Nanda et al., 2009; Oswald et
al., 2009; Ding et al., 2010). Therefore, we next examined the
responses of cholinergic interneurons to short trains of highfrequency stimuli (5 pulses at 40 Hz) delivered independently to
cortex and thalamus. Short-latency interneuron responses could
be readily discriminated after one or more pulses of the stimulation trains (Fig. 5 A, B). Cortical stimulation led to more spikes
being fired in response to the first pulse, followed by a gradual
decrease in short-latency firing probability throughout the
stimulus train (Fig. 5C), which is consistent with interneuron
responses to the paired-pulse stimulation at 10 Hz (Fig. 4). Conversely, the short-latency firing probability increased through the
stimulus train in response to thalamic train stimulation, with the
maximum response after the third pulse of the stimulus (Fig. 5D).
The difference in firing probability for the first cortical stimulation pulse and the mean of the following stimuli (pulses 2–5)
narrowly missed significance ( p ⫽ 0.05, Wilcoxon signed-rank
test; Fig. 5E), but the difference was highly significant when the
response was normalized to give the number of spikes as a percentage of spikes fired across all pulses, thus taking into account
baseline firing rate (Fig. 5F ). The firing probability for the first
thalamic stimulation was significantly lower than the mean of the
following stimuli (pulses 2–5) for both raw and normalized mea-
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3109
sures (Fig. 5 E, F ). Because of this facilitation of firing through the thalamic
stimulation train, and despite having a
lower probability of firing to the first
pulse, thalamic 40 Hz stimulation led to a
significantly greater number of evoked
spikes for the whole stimulation period
(0 –125 s) compared with firing evoked by
cortical stimulation ( p ⬍ 0.05, Mann–
Whitney U test). The cumulative sum of
the spikes at each pulse demonstrated the
greater number of spikes at the end of
the thalamic stimulus train (Fig. 5G), so
the slope of this line was significantly
steeper for thalamic than cortical stimulation (Fig. 5H ). It is noteworthy that not
only did the firing probability increase in
response to thalamic stimulation, but at
its peak (i.e., the third pulse), it reached
the same level (or higher) as that of the
first cortical stimulus pulse (Fig. 5E). In
summary, the probability of cholinergic
interneurons firing in response to the
stimulation of excitatory afferents was
therefore highly dependent on history
(the preceding inputs) and the source of
input activity (cortical vs thalamic).
The stimulation currents applied to
cortex and thalamus were not significantly different in the single, paired-pulse,
or high-frequency stimulation conditions
(Mann–Whitney, p ⬎ 0.05). Differences
in the responses of cholinergic interneurons to cortical and thalamic stimulation
were therefore not due to a systematic difference in the strength of stimulation.
Figure 3. Short-latency responses of cholinergic interneurons to cortical and thalamic stimulation. Ai, Unit-activity recording
(single representative sweep of stimulation artifacts and evoked responses, arrow indicates stimulation onset) of a cholinergic
interneuron that fired at short latency (⬃10 ms) in response to single-pulse electrical stimulation of the cortex. The coincident
ECoG is shown below; note evoked potential. Aii, Expanded view of the same response showing that, after the short-latency spike,
there is a cessation of firing (⬃250 ms) followed by a period of renewed spiking. B, PSTHs (2 ms bins) of the same interneuron’s
response to cortical stimulation (single pulses delivered at 0 ms, with artifact removed). Inset, Response during the first 50 ms after
stimulation. C, Mean PSTH of all cholinergic interneurons that showed a significant response to cortical stimulation (n ⫽ 16). Inset,
Responses of each interneuron (thin lines) during the first 50 ms after stimulation. Di, The same interneuron (as in A) also fired at
short latency (⬃10 ms) in response to single-pulse electrical stimulation of the thalamus. A second spike follows after ⬃40 ms.
Dii, Expanded view highlighting a later pause in firing that is followed by renewed spiking. E, PSTHs (2 ms bins) of the same
interneuron’s response to thalamic stimulation (single pulses delivered at 0 ms). Inset, Response during the first 50 ms after
stimulation. F, Mean PSTH for all interneurons that responded significantly to thalamic stimulation (n ⫽ 9). Note the evoked
increase in firing between 25 and 50 ms (arrowhead) that is not present after cortical stimulation (see C). G, Latencies of the first
spikes evoked at short latency (lag of 1.5–20 ms) of all interneurons significantly responding to either cortical or thalamic stimulation. Box plots show the medians (white line), the interquartile ranges (box), and extremes of the range (whiskers, within 99%
of the distribution). Dots show the mean latency of each individual interneuron. H, Latencies of the first spikes evoked at short
latency in all interneurons significantly responding to both cortical and thalamic stimulation. Lines join data from individual
interneurons.
Multiphasic responses of cholinergic
interneurons to cortical and
thalamic stimulation
Our anatomical results provided a
structural substrate for the short-latency
increases in firing of cholinergic interneurons in response to cortical and thalamic
stimulation. In behaving animals, however, the majority of studies on TANs (i.e.,
presumed cholinergic interneurons) have
focused on the pause in their firing and
subsequent rebound firing in response to
salient stimuli (Aosaki et al., 1994; Morris
et al., 2004). Most of the identified cholinergic interneurons we recorded in rats
also displayed multiphasic responses after
excitatory afferent stimulation (Figs. 1, 3,
4, 5). As described previously, the three
most prominent phases of the response
were an initial increase in firing occurring
shortly after stimulation, followed by a
decrease or cessation of firing, and then a
renewed or rebound increase in firing rate
compared with baseline. To facilitate the
comparison of data from rat and monkeys
(see below), we term these three phases
3110 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
“initial excitation,” “pause,” and “rebound,” respectively. Note that the initial
excitation is defined here as the number of
spikes fired directly after stimulation (and
before the pause), not just those in the
short-latency window (⬍20 ms) that we
used above to infer putative monosynaptic connectivity. In some studies (Ding et
al., 2010; Schulz and Reynolds, 2013),
“burst” has been used to describe the initial excitation, but we refrain from using
this term because single trials were generally not accompanied by ⱖ2 spikes in this
phase. For each identified cholinergic interneuron, we first defined which of these
phases occurred in the PSTH for singlepulse and/or high-frequency train stimulation of the cortex and/or thalamus and
then classified them by response type accordingly (Fig. 6). The majority of interneurons displayed all three phases in
response to both single-pulse and 40 Hz
stimulation of cortex (Fig. 6 A, B), although approximately one-third of interneurons had the pause and rebound Figure 4. Paired-pulse stimulation of cortex, but not thalamus, leads to a decrease in the evoked firing probability of cholinergic
response phases after single-pulse stimu- interneurons. A, Mean peristimulus histogram of all cholinergic interneurons that showed a significant short-latency response to
lation (Fig. 6A). The majority of cholin- paired cortical stimulation (n ⫽ 10). Inset, Magnification of the first 50 ms after stimulation. B, Mean peristimulus histogram of all
ergic interneuron responses to thalamic cholinergic interneurons that showed a significant short-latency response to paired thalamic stimulation (n ⫽ 9). Inset, Magnifistimulation (79%) also had initial excita- cation of the first 50 ms after stimulation. C, Short-latency firing probabilities for first and second pulses of paired cortical stimuli.
tion/pause/rebound phases, but this Dots show the mean firing probability of each individual interneuron. On average, firing probability to the second pulse was
changed markedly during high-frequency significantly lower (asterisk, Wilcoxon signed-rank, p ⬍ 0.005). D, Short-latency firing probabilities of each interneuron to the first
stimulation, in which only 22% of re- and second pulses of paired thalamic stimuli. On average, the firing probabilities to the first and second pulses were similar
sponses displayed the rebound phase (Fig. (Wilcoxon signed-rank test, p ⬎ 0.05).
6C,D). The pause was, therefore, almost
the initial excitation window, but was often followed by intense
ubiquitous after single-pulse or high-frequency train stimulation
rebound firing (Fig. 7 A, B, bottom trials of raster plots). In conof excitatory afferents. More often than not, pauses were pretrast, in trials with relatively long pauses, the pause was often
ceded by an initial excitation. In contrast, rebound firing was
preceded by one or more spikes in the initial excitation window,
uncommon after high-frequency thalamic stimulation, which
but was followed by little or no rebound firing (Fig. 7 A, B, top
also resulted in the highest amount of initial excitation.
trials of raster plots). When trials over all cholinergic interneuThe prevalence of pause and rebound phases of interneuron
rons were separated based on the number of spikes in the initial
responses to electrical stimulation of thalamus and cortex sugexcitation phase and the mean PSTH recalculated for all trials and
gests that, through interaction with intrinsic cellular and/or cirall neurons (cortex and thalamus stimulation combined for analcuit mechanisms, monosynaptic excitation of cholinergic
ysis), the initial excitation and rebound peaks in the PSTH scaled
interneurons may also lead to multiphasic responses. We used
negatively (Fig. 7C). Accordingly, across cortical and thalamic
the variation in stimulation-evoked spiking across all of our stimresponses in individual interneurons, the mean number of spikes
ulation protocols to test the hypothesis that the temporal profile
fired in the initial excitation phase was positively correlated with
of the multiphasic response was dependent on the level of initial
the mean pause duration (Fig. 7D), but negatively correlated with
excitation. To compare our findings in rat with those in behaving
the increase in firing during the rebound phase (Fig. 7E). The
monkeys, in which it was not possible to discriminate between
pause duration and rebound magnitude were not significantly
cortical and thalamic inputs, we looked for relationships with
correlated (Fig. 7F ). Therefore, in summary, the initial excitation
excitation per se (i.e., those that were consistent across stimulaafter stimulation of excitatory afferents was positively correlated
tion site and protocol). Previous investigations have demonwith the duration of the pause, with more spikes resulting in a
strated that the length of the pause phase of rodent interneurons
longer pause, and negatively correlated with the increase in firis dependent on the amount of spiking or depolarization after
ing during the rebound phase. The same phenomena could be
stimulation of cortical and thalamic axons (Oswald et al., 2009;
observed in sorted raster plots of cholinergic interneurons reDing et al., 2010). We investigated whether this phenomenon (as
sponding to high-frequency train stimulation of cortex and thalreflected in spiking) could also be seen in our in vivo rat data and
amus (Fig. 7G,H ). For high-frequency stimulation, the
whether the variance in the initial excitation and pause phases
recalculated mean PSTH for trials with different numbers of
could also predict the magnitude of the rebound phase (Fig. 7).
spikes in the initial excitation phase (cortex and thalamus stimuRaster plots of individual interneurons responding to singlelation together) further indicated that the number of spikes in the
pulse cortical and thalamic stimulation, in which the trials have
initial excitation phase scaled positively with the pause length and
been sorted by pause duration, reveal that in trials with relatively
short pauses, the pause was often preceded by one or no spikes in
negatively with the magnitude of the rebound (Fig. 7I ). Notably,
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3111
and in contrast to similar experiments in
vitro (Ding et al., 2010), high-frequency
stimulation of cortex lead to pauses that
were longer that the mean interspike interval (i.e., pause/interspike interval ratio
of ⬎1; Fig. 7J ). Across cortical and thalamic responses combined, the mean
pause duration was positively correlated
with the mean number of spikes in the
initial excitation phase (Fig. 7J ). For highfrequency stimulation, the increase in firing in the rebound phase was negatively
correlated with both the mean spikes in
the initial excitation (Fig. 7K ) and the
length of the pause (Fig. 7L). Together,
these data show that the magnitude of the
initial excitation of cholinergic interneurons was positively correlated with the
length of their pauses and negatively correlated with the magnitude of their rebound firing.
Figure 5. Differential responses of cholinergic interneurons to high-frequency stimulation of cortex and thalamus. A, B, Unit-activity
recording (single representative sweep of stimulation artifacts and evoked responses, with arrows indicating stimulation onset) of a
cholinergicinterneuronthatfiredatshortlatency(⬃10ms)inresponseto40Hztrains(5pulses)ofelectricalstimulideliveredtothecortex
(A) or thalamus (B). Ci, Mean PSTH of all cholinergic interneurons (n ⫽ 9) that showed significant short-latency responses during 40 Hz
cortical stimulation. Cii, Magnified view of Ci during the first 150 ms after the start of train stimulation. Di, Mean PSTH of all cholinergic
interneurons (n ⫽ 9) that showed significant short-latency responses during 40 Hz thalamic stimulation. Dii, Magnified view of Di during
thefirst150msafterthestartoftrainstimulation.E,Meanfiringprobabilityofspikesfiredatshortlatencyoneachpulseforcortical(red)and
thalamic (blue) stimulation. The firing probability for the first thalamic pulse was significantly lower than the mean of the following four
pulses (Wilcoxon signed-rank test, p ⫽ 0.004). F, Mean percentage of spikes fired on each pulse for cortical (red) and thalamic (blue)
stimulation. The percentage of spikes fired after first thalamic pulse was significantly higher than the mean of the following four pulses
(Wilcoxonsigned-ranktest,p⫽0.027),whereasforcorticalstimulation,itwassignificantlylower(Wilcoxonsigned-ranktest,p⫽0.027).
G,Meancumulativesums(cusum)offiringofallinterneuronsinresponsetocortical(red)andthalamic(blue)stimulationovereachpulse.
H, Slopes of the cusum for each interneuron (dots) to cortical and thalamic stimulation trains. The slope was significantly steeper for
responses to thalamic stimulation (Mann–Whitney U test, p ⫽ 0.0078).
Multiphasic responses of tonically
active neurons in behaving primates
Our experiments in rats demonstrated
that the magnitude of the initial excitation
predicts the profile of the subsequent
phases of the response in identified cholinergic interneurons. We next tested
whether these relationships held true for
putative cholinergic neurons recorded in
behavioral situations. Therefore, we examined the multiphasic responses of
TANs in four monkeys in relation to motivationally salient stimuli delivered in
two different behavioral conditions: (1) a
visual stimulus that preceded reward delivery by a fixed duration (the “rewardpredicting stimulus” condition; 79 TANs)
and (2) the delivery of juice in the absence
of any predictive cue (reward-only, 130
TANs). The major types of TAN response
to motivationally salient stimuli were the
same as those for identified cholinergic interneuron responses to afferent stimulation, although the prevalence of each
response type varied across species (compare Figs. 6, 8). More specifically, in the
reward-predicting stimulus condition,
the mean response across all TANs clearly
displayed all three phases: initial excitation, pause, and rebound (Fig. 8A). However, only 30% of individual TANs
displayed all three phases in response to
the reward-predicting stimulus in the
PSTH (Fig. 8 B, Cii), whereas the majority
had only the pause and rebound phases
(Fig. 8 B, Ci). In contrast, the mean response to reward-only had a relatively
small initial excitation phase and prominent pause and rebound phases (Fig. 8D)
and, accordingly, a smaller percentage
(19%) of TANs had all three response
3112 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
Figure 6. Multiphasic responses of cholinergic interneurons to stimulation of cortical and thalamic afferents. A, B, Classification of types of multiphasic responses to cortical stimulation. Ai,
Percentage of different response types evoked by single-pulse cortical stimulation. Aii, PSTHs of all interneurons with the pause/rebound type of response (top) and the initial excitation/pause/
rebound type of response (bottom). Single stimuli were delivered at 0 ms. Bi, Percentage of different response types evoked by a high-frequency cortical stimulation (train of 5 pulses at 40 Hz). Bii,
PSTHs of the one interneuron that displayed a pause/rebound response (top) and all the interneurons with initial excitation/pause/rebound responses (bottom). Start of train of high-frequency
stimuli at 0 ms. C, D, Classification of types of multiphasic responses to thalamic stimulation. Ci, Percentage of different responses types to single-pulse thalamic stimulation. Cii, PSTHs of the only
interneuron with a pause/rebound response (top) and all the interneurons that displayed initial excitation/pause/rebound responses (bottom). Di, Percentage of different responses types evoked by a
high-frequency thalamic stimulation. Dii, PSTHs of all interneurons with initial excitation/pause responses (top) and two neurons that displayed initial excitation/pause/rebound responses (bottom).
phases (Fig. 8 E, Fii). As for the reward-predicting stimulus, the
majority of responses to reward-only were pause/rebound (Fig.
8 E, Fi).
We then analyzed the different response phases of these monkey TANs using the same analytical framework as we used for
quantifying the responses of rat interneurons to afferent stimulation (Fig. 7). For the reward-predicting stimulus, raster plots
sorted by pause duration showed that, within the responses of
single neurons, increased levels of spiking in the initial excitation
window appeared to be followed by longer pauses and higher
rebound firing regardless of whether there was a significant peak
of initial excitation in the PSTH (Fig. 9 A, B). When trials over all
TANs were separated based on the number of spikes in the initial
excitation phase and the mean PSTH recalculated, the magnitude
of the rebound peak in the PSTH scaled negatively with the initial
excitation magnitude (Fig. 9C). In this condition, the mean number of spikes in the initial excitation phase of each neuron was
strongly positively correlated with the length of the pause phase
(Fig. 9D). Moreover, the increase in firing rate in the rebound
period was negatively correlated with the number of spikes in the
initial excitation phase (Fig. 9E) and, to a lesser extent, with the
pause length (Fig. 9F ). This indicates that, in the behaving primate, the number of spikes fired shortly after presentation of a
reward-predicting stimulus predicts the length and magnitude of
the subsequent pause and rebound phases, respectively. We used
a partial correlation analysis to assess whether the spontaneous
firing rate could explain these relationships; for example, how
much of the correlation between the initial excitation and pause/
rebound magnitude can be explained by their shared correlation
with firing rate. All of the correlations above were still significant
after partial correlation with the firing rate (Fig. 9D–F, values in
parentheses), suggesting that it was not a confounding factor.
In contrast to the case of reward-predicting stimuli, PSTHs
sorted by pause duration in the reward-only condition displayed
no obvious relationship between the different response phases
(Fig. 9G,H ). When the population PSTH was plotted for all the
trials with the same number of spikes in the initial excitation
phase, there was no difference in the magnitude of the rebound
phase (Fig. 9I ). Although there was a significant positive correlation between the mean number of spikes in the initial excitation
phase and the length of the pause, it was no longer significant
after partial correlation with the firing rate (Spearman correlation coefficient, p ⬎ 0.05). In addition, there were no significant
correlations between the change in rate in the rebound phase and
the mean number of spikes in the initial excitation or the length
of the pause (Fig. 9 K, L).
The mean latency of spikes in the initial excitation phase was
significantly longer for the reward-only condition (89 ⫾ 5.7 ms)
compared with that in the reward-predicting stimulus condition
(66.1 ⫾ 5 ms; Mann–Whitney test, p ⫽ 0.009). Because the onset
of the initial excitation to reward-only was slower than that to the
reward-predicting stimulus, which might partly arise because of
the lower temporal precision of the unpredicted reward, the inclusion of spikes directly after presentation (before the true response) could have diluted the initial excitation phase and
reduced the chances of significant correlations. We tested this
hypothesis by running various analyses, such as excluding the
first 30 –50 s after stimulus presentation or by using fixed time
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3113
Figure 7. Initial excitation predicts the temporal profile of the multiphase response in cholinergic interneurons. A, Raster plot with trials sorted by pause duration (top) and PSTH (bottom) for a
cholinergic interneuron responding to single-pulse cortical stimulation. B, As in A, for the same neuron responding to single-pulse thalamic stimulation. C, Mean PSTHs across all responses (cortical
and thalamic) sorted for the numbers of spikes in the initial excitation phase. Data from single-pulse stimulation of cortex and thalamus are combined. Responses were only included for a given
neuron if there were ⱖ3 trials with the requisite number of spikes in the initial excitation. Number of spikes in the initial excitation phase is shown using color code and the numbers of responses
that were averaged are shown in parentheses. D, Scatter plot of the mean number of spikes fired in the initial excitation phase and the mean normalized pause length for all interneurons (dots) after
single-pulse electrical stimulation of cortex (red) and thalamus (blue). The mean number of spikes in the initial excitation phase was positively correlated with the duration of the pause phase. Dotted
line shows the best linear fit between the two variables. E, F, Change in firing rate in the rebound phase was significantly negatively correlated with the mean number of spikes in the initial excitation
phase (E), but not significantly correlated with the pause duration (F). G, H, Identical plots as A and B but for a different interneuron responding to high-frequency stimulation of cortex (E) and
thalamus (F). I, Mean PSTHs across all trials with the same numbers of spikes in the intitial excitation phase for high-frequency stimulation of cortex and thalamus combined. Format as in C. J, Scatter
plot of the mean number of spikes fired in the initial excitation phase and the mean normalized pause length for all neurons after cortical (red) and thalamic (blue) high-frequency electrical
stimulation. The mean number of spikes in the initial excitation phase was positively correlated with the length of the pause phase across cortical and thalamic responses to stimulation. Dotted line
shows the best linear fit between the two variables. K, L, The change in firing rate in the rebound phase was significantly negatively correlated with the mean number of spikes in the initial excitation
phase (K) and with the pause duration (L; format as in J). Spearman correlation coefficients were used in all cases. NS, Not significant.
windows in relation only to the PSTH pause onset (e.g., counting
all spikes 100 ms before the PSTH pause onset), rather than
counting all the spikes after stimulus presentation to define the
initial excitation phase (data not shown). These changes to the
analysis did not lead to significant correlations between the initial
excitation phase with the pause length (after partial correlation with
firing rate) or rebound magnitude, suggesting that differences in the
onset of the initial excitation did not account for the differences in
response phase correlations across behavioral conditions.
Across all the TANs in both conditions, the values for the
mean spikes in the initial excitation, pause length, and rebound
rate increase were not significantly different between the rewardpredicting stimulus and reward-only conditions when calculated
using trial-by-trial analysis (Mann–Whitney U test, p ⬎ 0.05).
Therefore, the main difference between the two conditions was
the relationship between the different phases, rather than the
durations/magnitudes of the individual phases. In summary, and
as we observed in rat cholinergic neurons, the temporal profile of
the multiphasic response of primate TANs could be predicted by
the magnitude of the initial excitation. However, these correlations were only observed after reward-predicting stimuli, but
were weak or absent in response to free reward delivery outside of
a task context. Therefore, synaptic excitation by cortical and/or
thalamic afferents helps explain the evolution of the multiphasic
response in primate TANs under specific behavioral conditions.
Discussion
Cholinergic interneurons are key modulators of striatal microcircuit function. Their output is determined by the interplay of
intrinsic membrane properties underlying their autonomous fir-
3114 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
Figure 8. Multiphasic responses of primate TANs to motivationally salient stimuli. A, Mean response (Ai) and the percentage of significant responses per bin (Aii) across the population of recorded
TANs after the reward-predicting stimulus (given at 0 ms). B, Classification of the types of multiphasic responses of all the TANs recorded in this first behavioral condition. C, PSTHs of all TANs with
pause/rebound responses (Ci) and initial excitation/pause/rebound responses (Cii) to the reward-predicting stimulus. D, Mean response (Di) and the percentage of significant responses (Dii) across
the population of recorded TANs after reward-only. E, Classification of multiphasic responses of all of the TANs recorded in this second behavioral condition. F, PSTHs of all TANs with pause/rebound
responses (Fi) and initial excitation/pause/rebound responses (Fii) to reward-only.
ing (Bennett et al., 2000) and their synaptic inputs, which can
alter spike rate and timing (Bennett and Wilson, 1998). Cholinergic interneurons commonly respond to motivationally salient
stimuli with a pause in firing followed by a rebound increase in
firing rate (Aosaki et al., 1994; Morris et al., 2004). Here, we
demonstrate in the rat that the cortex and thalamus provide an
initial excitation to identified cholinergic interneurons that can
mediate the temporal profile of subsequent response phases and
that, by extrapolation to TANs in monkeys, this influence is present and selective for behavioral condition.
One of the aims of this study was to quantify cortical and
thalamic synaptic innervation of cholinergic interneurons. We
found that an individual neuron can form synapses with cortical
terminals and thalamic terminals, which can be with proximal
dendrites. Overall, we found that thalamic terminals are more
numerous than cortical terminals, which is consistent with previous studies (Lapper and Bolam, 1992). Despite attempts at controlling for antibody labeling, we cannot rule out the possibility
that some of the terminals are false-negatives for the VGluT
markers; however, it has been indicated that a proportion of terminals forming asymmetric synapses in the striatum are negative
for both VGluT1 and VGluT2 (Lacey et al., 2005). This sparse
excitatory, and in particular, cortical innervation does not mean
that these inputs do not have significant effects, a point that is
clear from the current and previous in vivo stimulation data (Wilson et al., 1990). Sparse inputs may have a particular role in
regulating networks (Teramae et al., 2012).
Despite the apparently sparse nature of cortical inputs, we
confirm that brief, single-pulse electrical stimulation of cortex
often evokes short-latency spiking (Wilson et al., 1990; Reynolds
and Wickens, 2004; Sharott et al., 2012). Thalamic inputs, and
especially those arising from caudal ITN, are assumed to partly
determine cholinergic interneuron activity in vivo (Schulz and
Reynolds, 2013). We found that short-latency interneuron responses to matched stimulation of thalamus were similarly
timed, but less robust compared with those driven by cortex.
However, with each pulse of a high-frequency stimulus train,
interneuron responses to thalamic inputs became increasingly
robust, whereas responses to cortical inputs were progressively
dampened. These contrasting response properties have important functional implications. For example, cortical and thalamic
synapses with cholinergic interneurons might be subject to different short-term plasticity rules, at least in vivo (Ding et al.,
2010). The mechanisms underlying this possible scenario are unknown. Nevertheless, attenuation of cortically-driven spiking
with repeated input would constrain the influence of cortical
inputs on short-latency acetylcholine release regardless of the
strength of sustained input from a given cortical area. In contrast,
spiking in response to salient/orienting inputs from the ITN
would scale positively with the strength and duration of thalamic
input. The short half-life of synaptically released acetylcholine,
together with the fast kinetics of nicotinic acetylcholine receptors, would help to ensure accurate striatal “readout” of these
distinct responses, which could support the important role of
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3115
Figure 9. Dependence of multiphase responses of primate TANs on their initial excitation is behaviorally specific. A, Raster plot with trials sorted by pause duration (top) and PSTH (bottom) for
a TAN responding to the reward-predicting stimulus with an initial excitation/pause/rebound response. B, Plots for a different TAN responding to the same condition with a pause/rebound response.
C, Mean PSTHs for all trials with the same number of spikes in the initial excitation phase, in response to the reward-predicting stimulus. Responses were only included for a given TAN if there were
ⱖ3 trials with the requisite number of spikes in the initial excitation. Number of spikes in the initial excitation phase is shown using color code and the number of TANs that were averaged is shown
in parenthesis. D, Mean number of spikes in the initial excitation was positively correlated with the length of the pause phase across all neurons after partial correlation with firing rate (parentheses).
E, F, Increase in firing rate in the rebound phase was significantly negatively correlated and the mean number of spikes in the initial excitation phase (E) and with the length of the pause (F). Both
correlations were significant after partialization with firing rate (parentheses). G, Raster plot with trials sorted by pause duration (top) and PSTH (bottom) for a TAN responding to reward-only with
an initial excitation/pause/rebound response. H, Identical plots for a different TAN responding to the same condition with a pause/rebound response. I, Mean PSTH for all neurons for trials with the
same numbers of spikes in the initial excitation phase, in response to the unpredicted reward. Format as in C. J, Mean number of spikes in the initial excitation phase was correlated with the length
of the pause phase across all neurons, but was no longer significant after partial correlation with firing rate (parentheses). K, L, Increase in firing rate in the rebound phase was not significantly
correlated with the mean number of spikes in the initial excitation phase (K) or with the length of the pause (L). Spearman correlation coefficients were used in all cases. NS, Not significant.
these thalamic inputs for learning and behavioral flexibility
(Brown et al., 2010; Bradfield et al., 2013). Although cortical
modulation of cholinergic interneurons has not been studied in
behaving animals, diverse information carried by their cortical
and thalamic afferents could play different roles in modulating
their output and influence on behavior.
Importantly, we define a novel relationship between initial
spiking and the multiphasic responses of cholinergic interneurons to stimulation of cortical/thalamic afferents. The two excitatory inputs did not produce specific multiphasic responses, but
rather, the amount of initial excitation, regardless of the input
source, predicted the temporal profile of the subsequent pause
and rebound phases. However, because the properties of the initial excitation were different (cortex and thalamus being broadly
depressing and facilitating, respectively), the nature of the multiphasic response was determined partly by its source. In the case
of responses to cortical stimulation, the attenuation of shortlatency firing during high-frequency stimulation meant that rebound phases were the rule. Cortical afferents are therefore well
suited to mediating a consistent pause length and a strong rebound. In contrast, sustained thalamic input favored more shortlatency spikes and, therefore, long pauses with little or no
subsequent rebound. The nature of excitatory input can therefore
determine acetylcholine release in striatum for hundreds of milliseconds after the short-latency modulation of spiking.
We also recorded the multiphasic responses of monkey TANs
to motivationally salient stimuli and demonstrate that the correlations in initial spiking, pause, and rebound response phases as
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
3116 • J. Neurosci., February 19, 2014 • 34(8):3101–3117
defined in rat hold true for primates under specific behavioral
conditions. The pause in firing after rewarding stimuli has become another distinguishing physiological feature of TANs
(Kimura et al., 1984; Apicella et al., 1991) and might provide a
temporal framework for reinforcement learning (Morris et al.,
2004). Importantly, the rebound phase scales with reward-based
task performance (Apicella et al., 2011). We found that the number of spikes in the initial excitation phase was predictive of both
the pause and rebound phases of the TAN response to a rewardpredicting stimulus. By extrapolating from our findings in rats,
cortical and/or thalamic afferents emerge as key candidate drivers
of the initial spiking phase of the responses of primate TANs to
the reward-predicting stimulus. However, in the reward-only
condition, correlations between TAN response phases were absent or weak, suggesting that responses to unpredicted reward
might be underlain by different circuits/mechanisms. In both
behavioral conditions, cholinergic transmission could modulate
striatal dopamine release directly (Cachope et al., 2012; Threlfell
et al., 2012) to further influence the processing of reward-based
tasks. It will be important to test in future studies whether the
principles defined here also apply to the ventral striatum.
A positive correlation between the initial spiking and pause
duration of rodent interneurons has been shown in vitro (Oswald
et al., 2009; Ding et al., 2010) and is a consequence of interactions
between synaptic excitation and intrinsic currents. Indeed,
excitatory inputs to these interneurons are reliably followed by
an intrinsically generated afterhyperpolarization (AHP) that
transiently suppresses their tonic firing (Oswald et al., 2009).
Moreover, input magnitude and AHP duration are positively
correlated (Oswald et al., 2009; Schulz et al., 2011). This mechanism likely explains the relationship between the initial excitation
and pause phases of cholinergic interneurons in our stimulation
experiments in rats and could also underlie the same response
phases of TANs after reward-predicting stimuli. Conversely, an
unambiguous dissection of whether and how rebound firing
might emerge from synaptic excitation-AHP sequences is lacking
(Schulz and Reynolds, 2013), a scenario compounded by the absence of rebound interneuron firing after afferent stimulation in
previous experiments in vivo and in vitro (Oswald et al., 2009;
Ding et al., 2010; Schulz et al., 2011). One proposal is that the
rebound reflects a separate and subsequent excitation from cortex and/or thalamus (Schulz and Reynolds, 2013). A specialized
population of ITN cells that respond at long latencies to orienting
stimuli could subserve this late excitation (Matsumoto et al.,
2001; Schulz and Reynolds, 2013). The co-release of glutamate by
cholinergic interneurons (Higley et al., 2011) might also shape
their multiphasic responses through feedforward excitation.
However, this seems unlikely for some relationships defined here;
for example, the initial excitation and rebound phases were negatively correlated. Overall, our findings support the possibility
that a brief excitatory drive can initiate a sequence of intrinsic
and/or local circuit events that trigger both the pause and the
rebound, but in a way that ensures that these two response phases
are negatively correlated.
The correlations between TAN response phases were clear
after reward-predicting stimuli but not after unpredicted rewards. This raises the possibility that the two behavioral conditions recruited distinct sets of inputs to differentially influence
firing. We found that ⬃60% of synapses made are symmetric,
providing further evidence that GABAergic inputs likely play
crucial roles in modulating these cells. Indeed, inhibition of cholinergic interneurons by optogenetic stimulation of their
GABAergic inputs can produce rebound responses (English et al.,
2011; Brown et al., 2012). Therefore, the pause in the reward-only
condition has several possible sources of GABAergic inhibition,
such as axon collaterals of MSNs (Gonzales et al., 2013), GABAergic striatal interneurons (Sullivan et al., 2008; Gonzales et al.,
2013), and GABAergic projection neurons in the external globus
pallidus (Mallet et al., 2012) and midbrain (Brown et al., 2012).
The idea that inputs from midbrain could mediate TAN responses to reward would fit with the role of these distal structures
in processing reward-related stimuli. Moreover, the intrinsic
membrane properties of cholinergic interneurons homogenize
the length of their pauses to hyperpolarizing inputs of varying
strength (Wilson, 2005), which could disassociate the strength of
inhibitory inputs from the magnitude of the rebound.
Elucidating how the dynamic spiking of striatal cholinergic
interneurons is governed by their myriad synaptic inputs is critical for fully understanding their functional roles in striatal microcircuits and contributions to adaptive behavior. With this
mind, we conclude that cortex and thalamus can provide an initial synaptic excitation that shapes the multiphasic responses of
these interneurons to motivationally salient stimuli under specific behavioral conditions.
References
Adler A, Finkes I, Katabi S, Prut Y, Bergman H (2013a) Encoding by synchronization in the primate striatum. J Neurosci 33:4854 – 4866. CrossRef
Medline
Adler A, Katabi S, Finkes I, Prut Y, Bergman H (2013b) Different correlation
patterns of cholinergic and GABAergic interneurons with striatal projection neurons. Front Syst Neurosci 7:47. CrossRef Medline
Aosaki T, Tsubokawa H, Ishida A, Watanabe K, Graybiel AM, Kimura M
(1994) Responses of tonically active neurons in the primate’s striatum
undergo systematic changes during behavioral sensorimotor conditioning. J Neurosci 14:3969 –3984. Medline
Apicella P (2007) Leading tonically active neurons of the striatum from reward detection to context recognition. Trends Neurosci 30:299 –306.
CrossRef Medline
Apicella P, Scarnati E, Schultz W (1991) Tonically discharging neurons of
monkey striatum respond to preparatory and rewarding stimuli. Exp
Brain Res 84:672– 675. Medline
Apicella P, Legallet E, Trouche E (1997) Responses of tonically discharging
neurons in the monkey striatum to primary rewards delivered during
different behavioral states. Exp Brain Res 116:456 – 466. CrossRef Medline
Apicella P, Ravel S, Deffains M, Legallet E (2011) The role of striatal tonically active neurons in reward prediction error signaling during instrumental task performance. J Neurosci 31:1507–1515. CrossRef Medline
Bennett BD, Wilson CJ (1998) Synaptic regulation of action potential timing in neostriatal cholinergic interneurons. J Neurosci 18:8539 – 8549.
Medline
Bennett BD, Callaway JC, Wilson CJ (2000) Intrinsic membrane properties
underlying spontaneous tonic firing in neostriatal cholinergic interneurons. J Neurosci 20:8493– 8503. Medline
Bolam JP, ed (1992) Experimental neuroanatomy. Oxford: OUP.
Bradfield LA, Bertran-Gonzalez J, Chieng B, Balleine BW (2013) The
thalamostriatal pathway and cholinergic control of goal-directed action:
interlacing new with existing learning in the striatum. Neuron 79:153–
166. CrossRef Medline
Brown HD, Baker PM, Ragozzino ME (2010) The parafascicular thalamic
nucleus concomitantly influences behavioral flexibility and dorsomedial
striatal acetylcholine output in rats. J Neurosci 30:14390 –14398. CrossRef
Medline
Brown MT, Tan KR, O’Connor EC, Nikonenko I, Muller D, Lüscher C
(2012) Ventral tegmental area GABA projections pause accumbal cholinergic interneurons to enhance associative learning. Nature 492:452–
456. CrossRef Medline
Cachope R, Mateo Y, Mathur BN, Irving J, Wang HL, Morales M, Lovinger
DM, Cheer JF (2012) Selective activation of cholinergic interneurons
enhances accumbal phasic dopamine release: setting the tone for reward
processing. Cell Rep 2:33– 41. CrossRef Medline
Deffains M, Legallet E, Apicella P (2010) Modulation of neuronal activity in
Doig et al. • Cholinergic Interneurons and Synaptic Excitation
the monkey putamen associated with changes in the habitual order of
sequential movements. J Neurophysiol 104:1355–1369. CrossRef Medline
Dimova R, Vuillet J, Nieoullon A, Kerkerian-Legoff L (1993) Ultrastructural features of the choline acetyltransferase-containing neurons and
relationships with nigral dopaminergic and cortical afferent pathways in
the rat striatum. Neuroscience 53:1059 –1071. CrossRef Medline
Ding JB, Guzman JN, Peterson JD, Goldberg JA, Surmeier DJ (2010) Thalamic gating of corticostriatal signaling by cholinergic interneurons. Neuron 67:294 –307. CrossRef Medline
Doig NM, Moss J, Bolam JP (2010) Cortical and thalamic innervation of
direct and indirect pathway medium-sized spiny neurons in mouse striatum. J Neurosci 30:14610 –14618. CrossRef Medline
Dubé L, Smith AD, Bolam JP (1988) Identification of synaptic terminals of
thalamic or cortical origin in contact with distinct medium-size spiny neurons in the rat neostriatum. J Comp Neurol 267:455– 471. CrossRef Medline
English DF, Ibanez-Sandoval O, Stark E, Tecuapetla F, Buzsáki G, Deisseroth
K, Tepper JM, Koos T (2011) GABAergic circuits mediate the
reinforcement-related signals of striatal cholinergic interneurons. Nat
Neurosci 15:123–130. CrossRef Medline
Gonzales KK, Pare JF, Wichmann T, Smith Y (2013) GABAergic inputs
from direct and indirect striatal projection neurons onto cholinergic interneurons in the primate putamen. J Comp Neurol 521:2502–2522.
CrossRef Medline
Henny P, Brown MT, Northrop A, Faunes M, Ungless MA, Magill PJ, Bolam JP
(2012) Structural correlates of heterogeneous in vivo activity of midbrain
dopaminergic neurons. Nat Neurosci 15:613– 619. CrossRef Medline
Henny P, Brown MT, Micklem BR, Magill PJ, Bolam JP (2013) Stereological
and ultrastructural quantification of the afferent synaptome of individual
neurons. Brain Struct Funct, in press. CrossRef
Higley MJ, Gittis AH, Oldenburg IA, Balthasar N, Seal RP, Edwards RH,
Lowell BB, Kreitzer AC, Sabatini BL (2011) Cholinergic interneurons
mediate fast VGluT3-dependent glutamatergic transmission in the striatum. PLoS One 6:e19155. CrossRef Medline
Inokawa H, Yamada H, Matsumoto N, Muranishi M, Kimura M (2010) Juxtacellular labeling of tonically active neurons and phasically active neurons in
the rat striatum. Neuroscience 168:395– 404. CrossRef Medline
Jiao Y, Sun Z, Lee T, Fusco FR, Kimble TD, Meade CA, Cuthbertson S, Reiner
A (1999) A simple and sensitive antigen retrieval method for freefloating and slide-mounted tissue sections. J Neurosci Methods 93:149 –
162. CrossRef Medline
Joshua M, Adler A, Mitelman R, Vaadia E, Bergman H (2008) Midbrain dopaminergic neurons and striatal cholinergic interneurons encode the difference
between reward and aversive events at different epochs of probabilistic classical conditioning trials. J Neurosci 28:11673–11684. CrossRef Medline
Kimura M, Rajkowski J, Evarts E (1984) Tonically discharging putamen
neurons exhibit set-dependent responses. Proc Natl Acad Sci U S A 81:
4998 –5001. CrossRef Medline
Kusnoor SV, Parris J, Muly EC, Morgan JI, Deutch AY (2010) Extracerebellar role for Cerebellin1: modulation of dendritic spine density and synapses in striatal medium spiny neurons. J Comp Neurol 518:2525–2537.
CrossRef Medline
Lacey CJ, Boyes J, Gerlach O, Chen L, Magill PJ, Bolam JP (2005) GABA(B)
receptors at glutamatergic synapses in the rat striatum. Neuroscience 136:
1083–1095. CrossRef Medline
Lapper SR, Bolam JP (1992) Input from the frontal-cortex and the parafascicular nucleus to cholinergic interneurons in the dorsal striatum of the
rat. Neuroscience 51:533–545. CrossRef Medline
Llinas RR, Leznik E, Urbano FJ (2002) Temporal binding via cortical coincidence detection of specific and nonspecific thalamocortical inputs: a
voltage-dependent dye-imaging study in mouse brain slices. Proc Natl
Acad Sci U S A 99:449 – 454. CrossRef Medline
Magill PJ, Bolam JP, Bevan MD (2000) Relationship of activity in the subthalamic nucleus-globus pallidus network to cortical electroencephalogram. J Neurosci 20:820 – 833. Medline
Magill PJ, Sharott A, Bevan MD, Brown P, Bolam JP (2004) Synchronous
unit activity and local field potentials evoked in the subthalamic nucleus
by cortical stimulation. J Neurophysiol 92:700 –714. CrossRef Medline
Magill PJ, Pogosyan A, Sharott A, Csicsvari J, Bolam JP, Brown P (2006)
Changes in functional connectivity within the rat striatopallidal axis dur-
J. Neurosci., February 19, 2014 • 34(8):3101–3117 • 3117
ing global brain activation in vivo. J Neurosci 26:6318 – 6329. CrossRef
Medline
Mallet N, Le Moine C, Charpier S, Gonon F (2005) Feedforward inhibition
of projection neurons by fast-spiking GABA interneurons in the rat striatum in vivo. J Neurosci 25:3857–3869. CrossRef Medline
Mallet N, Pogosyan A, Márton LF, Bolam JP, Brown P, Magill PJ (2008)
Parkinsonian beta oscillations in the external globus pallidus and their
relationship with subthalamic nucleus activity. J Neurosci 28:14245–
14258. CrossRef Medline
Mallet N, Micklem BR, Henny P, Brown MT, Williams C, Bolam JP, Nakamura KC, Magill PJ (2012) Dichotomous organization of the external
globus pallidus. Neuron 74:1075–1086. CrossRef Medline
Matsumoto N, Minamimoto T, Graybiel AM, Kimura M (2001) Neurons in
the thalamic CM-Pf complex supply striatal neurons with information
about behaviorally significant sensory events. J Neurophysiol 85:960 –
976. Medline
Morris G, Arkadir D, Nevet A, Vaadia E, Bergman H (2004) Coincident but
distinct messages of midbrain dopamine and striatal tonically active neurons. Neuron 43:133–143. CrossRef Medline
Nanda B, Galvan A, Smith Y, Wichmann T (2009) Effects of stimulation of
the centromedian nucleus of the thalamus on the activity of striatal cells in
awake rhesus monkeys. Eur J Neurosci 29:588 –598. CrossRef Medline
Oswald MJ, Oorschot DE, Schulz JM, Lipski J, Reynolds JN (2009) IH current generates the afterhyperpolarisation following activation of subthreshold cortical synaptic inputs to striatal cholinergic interneurons.
J Physiol 587:5879 –5897. CrossRef Medline
Paxinos G, Watson C (1986) The rat brain in stereotaxic coordinates, Ed 2.
Sydney: Academic.
Ravel S, Legallet E, Apicella P (2003) Responses of tonically active neurons
in the monkey striatum discriminate between motivationally opposing
stimuli. J Neurosci 23:8489 – 8497. Medline
Reynolds JN, Wickens JR (2004) The corticostriatal input to giant aspiny interneurons in the rat: a candidate pathway for synchronising the response to
reward-related cues. Brain Res 1011:115–128. CrossRef Medline
Sadek AR, Magill PJ, Bolam JP (2007) A single-cell analysis of intrinsic connectivity in the rat globus pallidus. J Neurosci 27:6352– 6362. CrossRef
Medline
Schulz JM, Reynolds JN (2013) Pause and rebound: sensory control of cholinergic signaling in the striatum. Trends Neurosci 36:41–50. CrossRef
Medline
Schulz JM, Oswald MJ, Reynolds JN (2011) Visual-induced excitation leads
to firing pauses in striatal cholinergic interneurons. J Neurosci 31:11133–
11143. CrossRef Medline
Sharott A, Doig NM, Mallet N, Magill PJ (2012) Relationships between the
firing of identified striatal interneurons and spontaneous and driven cortical activities in vivo. J Neurosci 32:13221–13236. CrossRef Medline
Sizemore RJ, Reynolds JN, Oorschot DE (2010) Number and type of synapses on the distal dendrite of a rat striatal cholinergic interneuron: a
quantitative, ultrastructural study. J Anat 217:223–235. CrossRef Medline
Somogyi P, Bolam JP, Smith AD (1981) Monosynaptic cortical input and
local axon collaterals of identified striatonigral neurons. A light and electron microscopic study using the Golgi-peroxidase transportdegeneration procedure. J Comp Neurol 195:567–584. CrossRef Medline
Sullivan MA, Chen H, Morikawa H (2008) Recurrent inhibitory network
among striatal cholinergic interneurons. J Neurosci 28:8682– 8690.
CrossRef Medline
Teramae JN, Tsubo Y, Fukai T (2012) Optimal spike-based communication
in excitable networks with strong-sparse and weak-dense links. Sci Rep
2:485. CrossRef Medline
Threlfell S, Lalic T, Platt NJ, Jennings KA, Deisseroth K, Cragg SJ (2012)
Striatal dopamine release is triggered by synchronized activity in cholinergic interneurons. Neuron 75:58 – 64. CrossRef Medline
Wilson CJ (2005) The mechanism of intrinsic amplification of hyperpolarizations and spontaneous bursting in striatal cholinergic interneurons.
Neuron 45:575–585. CrossRef Medline
Wilson CJ, Chang HT, Kitai ST (1990) Firing patterns and synaptic potentials of identified giant aspiny interneurons in the rat neostriatum. J Neurosci 10:508 –519. Medline